IMRT Delivery Performance With a Varian Multileaf Collimator

Characterization of a novel VenusX orthogonal dual-layer multileaf collimator

PURPOSE

To investigate and characterize the performance of a novel orthogonal dual-layer alpha multileaf collimator (αMLC) mounted on the LinaTech VenusX linac.

METHODS

We evaluated leaf positioning accuracy and reproducibility using an electronic portal imaging device through the picket fence test. The average, interleaf, intraleaf, and leaf tip transmissions of the single and dual layers were measured using an ionization chamber. Square and rhombus fields were used to evaluate the leaf penumbra of αMLC. To investigate the advantages of the orthogonal dual-layer multileaf collimator (MLC) in field shaping, right triangular and circular pattern fields were formed using both the dual layers and single layers of the αMLC.

RESULTS

The average maximum positioning deviations of the upper and lower αMLC over 1 year were 0.76 ± 0.09 mm and 0.62 ± 0.07 mm, respectively. The average transmissions were 1.87%, 1.83%, and 0.03% for the upper-, lower- and dual-layer αMLC, respectively. The maximum interleaf transmissions of the lower- and dual-layer were 2.43% and 0.17%, respectively. The leaf tip transmissions were 9.34% and 0.25%, respectively. The penumbra of the square field was 6.2 mm in the X direction and 8.0 mm in the Y direction. The average penumbras of the rhombus fields with side lengths of 5 and 10 cm were 3.6 and 4.9 mm, respectively. For the right triangular and circular fields, the fields shaped by the dual-layer leaves were much closer to the set field than those shaped by single-layer leaves. The dose undulation amplitude of the 50% isodose lines and leaf stepping angle change of the dual-layer leaves were smaller than those of the single-layer leaves.

CONCLUSIONS

The αMLC benefits from its orthogonal dual-layer design. Leaf transmission, dose undulations at the field edge, and MLC field dependence of the leaf stepping angle of the dual-layer αMLC were remarkably reduced.

A method for patient-specific DVH verification using a high-sampling-rate log file in an Elekta linac

We have proposed a method for patient-specific dose-volume histogram (DVH) verification using a 40-ms high-sampling-rate log file (HLF) available in an Elekta linac. Ten prostate volumetric-modulated arc therapy plans were randomly selected, and systematic leaf position errors of ±0.2, ±0.4, or ±0.8 mm were added to the 10 plans, thereby producing a total of 70 plans. An RTP file was created by interpolating each leaf position in the HLF to obtain values at each control point, which is subsequently exported to a treatment planning system. The isocenter dose calculated by the HLF-based plan to a phantom (Delta4 Phantom+) was compared to that measured by the diode in the phantom in order to evaluate the accuracy of the HLF-based dose calculation. The D95 of the planning target volume (PTV) was also compared between the HLF-based plans and the original plans with the systematic leaf position errors, the latter being referred to as theory-based plans. Sensitivities of the DVH parameters in the target, the rectum, and the bladder were also calculated with the varied systematic leaf position errors. The relative differences in the isocenter doses between the HLF-based calculations and the measurements among the 70 plans were 0.21% ± 0.67% (SD). The maximum relative differences in PTV D95 between the HLF-based and the theory-based plans among the 70 cases were 0.11%. The patient-specific DVH verification method detected a change in the target DVH parameters of less than 1% when the systematic leaf position error was ±0.2 mm. It is therefore suggested that the proposed DVH verification method may simplify patient-specific dose quality assurance procedures without compromising accuracy and sensitivity.

Challenges in modeling the Agility multileaf collimator in treatment planning systems and current needs for improvement

BACKGROUND

The Agility multileaf collimator (MLC) mounted in Elekta linear accelerators features some unique design characteristics, such as large leaf thickness, eccentric curvature at the leaf tip, and defocused leaf sides ('tilting'). These characteristics offer several advantages but modeling them in treatment planning systems (TPSs) is challenging.

PURPOSE

The goals of this study were to investigate the challenges faced when modeling the Agility in two commercial TPSs (Monaco and RayStation) and to explore how the implemented MLC models could be improved in the future.

METHODS

Four linear accelerators equipped with the Agility, located at different centers, were used for the study. Three centers use the RayStation TPS and the other one uses Monaco. For comparison purposes, data from four Varian linear accelerators with the Millennium 120 MLC were also included. Average doses measured with asynchronous sweeping gap tests were used to characterize and compare the characteristics of the Millennium and the Agility MLCs and to assess the MLC model in the TPSs. The FOURL test included in the ExpressQA package, provided by Elekta, was also used to evaluate the tongue-and-groove with radiochromic films. Finally, raytracing was used to investigate the impact of the MLC geometry and to understand the results obtained for each MLC.

RESULTS

The geometry of the Agility produces dosimetric effects associated with the rounded leaf end up to a distance 20 mm away from the leaf tip end measured at the isocenter plane. This affects the tongue-and-groove shadowing, which progressively increases along the distance to the tip end. The RayStation and Monaco TPSs did not account for this effect, which made trade-offs in the MLC parameters necessary and greatly varied the final MLC parameters used by different centers. Raytracing showed that these challenging leaf tip effects were directly related to the MLC geometry and that the characteristics mainly responsible for the large leaf tip effects of the Agility were its tilting design and its small source-to-collimator distance.

CONCLUSIONS

The MLC models implemented in RayStation and Monaco could not accurately reproduce the leaf tip effects for the Agility. Therefore, trade-offs are needed and the optimal MLC parameters are dependent on the specific characteristics of treatment plans. Refining the MLC models for the Agility to better approximate the measured leaf tip and tongue-and-groove effects would extend the validity of the MLC model, reduce the variability in the MLC parameters used by the community, and facilitate the standardization of the MLC configuration process.

Impact of systematic MLC positional uncertainties on the quality of single-isocenter multi-target VMAT-SRS treatment plans

Purpose

To study the impact of systematic MLC leaf positional uncertainties (stemming from mechanical inaccuracies or sub‐optimal MLC modeling) on the quality of intracranial single‐isocenter multi‐target VMAT‐SRS treatment plans. An estimation of appropriate tolerance levels is attempted.

Methods

Five patients, with three to four metastases and at least one target lying in close proximity to organs‐at‐risk (OARs) were included in this study. A single‐isocenter multi‐arc VMAT plan per patient was prepared, which served as the reference for dosimetric impact evaluation. A range of leaf offsets was introduced (±0.03 mm up to ±0.30 mm defined at the MLC plane) to both leaf banks, by varying the leaf offset MLC modeling parameter in Monaco for all the prepared plans, in order to simulate projected leaf offsets of ±0.09 mm up to ±0.94 mm at the isocenter plane, respectively. For all offsets simulated and cases studied, dose distributions were re‐calculated and compared with the corresponding reference ones. An experimental dosimetric procedure using the SRS mapCHECK diode array was also performed to support the simulation study results and investigate its suitability to detect small systematic leaf positional errors.

Results

Projected leaf offsets of ±0.09 mm were well‐tolerated with respect to both target dosimetry and OAR‐sparing. A linear relationship was found between D_95% percentage change and projected leaf offset (slope: 12%/mm). Impact of projected offset on target dosimetry was strongly associated with target volume. In two cases, plans that could be considered potentially clinically unacceptable (i.e., clinical dose constraint violation) were obtained even for projected offsets as small as 0.19 mm. The performed experimental dosimetry check can detect potential small systematic leaf errors.

Conclusions

Plan quality indices and dose–volume metrics are very sensitive to systematic sub‐millimeter leaf positional inaccuracies, projected at the isocenter plane. Acceptable and tolerance levels in systematic MLC uncertainties need to be tailored to VMAT‐SRS spatial and dosimetric accuracy requirements.

Machine learning models to predict the delivered positions of Elekta multileaf collimator leaves for volumetric modulated arc therapy

PURPOSE

Accurate positioning of multileaf collimator (MLC) leaves during volumetric modulated arc therapy (VMAT) is essential for accurate treatment delivery. We developed a linear regression, support vector machine, random forest, extreme gradient boosting (XGBoost), and an artificial neural network (ANN) for predicting the delivered leaf positions for VMAT plans.

METHODS

For this study, 160 MLC log files from 80 VMAT plans were obtained from a single institution treated on 3 Elekta Versa HD linear accelerators. The gravity vector, X1 and X2 jaw positions, leaf gap, leaf position, leaf velocity, and leaf acceleration were extracted and used as model inputs. The models were trained using 70% of the log files and tested on the remaining 30%. Mean absolute error (MAE), root mean square error (RMSE), the coefficient of determination R² , and fitted line plots showing the relationship between delivered and predicted leaf positions were used to evaluate model performance.

RESULTS

The models achieved the following errors: linear regression (MAE = 0.158 mm, RMSE = 0.225 mm), support vector machine (MAE = 0.141 mm, RMSE = 0.199 mm), random forest (MAE = 0.161 mm, RMSE = 0.229 mm), XGBoost (MAE = 0.185 mm, RMSE = 0.273 mm), and ANN (MAE = 0.361 mm, RMSE = 0.521 mm). A significant correlation between a plan's gamma passing rate (GPR) and the prediction errors of linear regression, support vector machine, and random forest is seen (p < 0.045).

CONCLUSIONS

We examined various models to predict the delivered MLC positions for VMAT plans treated with Elekta linacs. Linear regression, support vector machine, random forest, and XGBoost achieved lower errors than ANN. Models that can accurately predict the individual leaf positions during treatment can help identify leaves that are deviating from the planned position, which can improve a plan's GPR.

Evaluation of QA software system analysis for the static picket fence test

Intensity modulation treatments are widely used in radiotherapy because of many known advantages. In this context, the picket fence test (PF) is a relevant test to check the Multileaf Collimator (MLC) performances. So this work compares and evaluates three analysis platforms for the PF used routinely by three different institutions. This study covers two linear accelerators (Linac) with two MLC types, a Millenium 120 MLC and Millenium 120 High Definition MLC respectively on a Varian Truebeam and Truebeam STx. Both linacs include an As 1200 portal imager (EPID). From a reference PF plan, MLC errors have been introduced to modify the slits in position or width (shifts from 0.1 to 0.5 mm on one or both banks). Then errors have been defined on the EPID to investigate detection system deviations (signal sensitivity and position variations). Finally, 110 DICOM‐RT images have been generated and analyzed by each software system. All software systems have shown good performances to quantify the position errors, even though the leaf pair identifications can be wrong in some cases regarding the analysis method considered. The slit width measurement (not calculated by all software systems) has shown good sensitivity, but some quantification difficulties have been highlighted regardless of the analysis method used. Linked to the expected accuracy of the PF test, the imager variations have demonstrated considerable influence in the results. Differences in the results and the analysis methods have been pointed out for each software system. The results can be helpful to optimize the settings of each analysis software system depending on expectations and treatment modalities of each institution.

Commissioning a multileaf collimator virtual cone for the stereotactic radiosurgery of trigeminal neuralgia

A multileaf collimator (MLC), virtual‐cone treatment technique has been commissioned for trigeminal neuralgia (TGN) at Tri‐Cities Cancer Center (TCCC). This novel technique was initially developed at the University of Alabama in Birmingham (UAB); it is designed to produce a spherical dose profile similar to a fixed, 5‐mm conical collimator distribution. Treatment is delivered with a 10‐MV flattening‐filter‐free (FFF) beam using a high‐definition MLC on a Varian Edge linear accelerator. Absolute dose output and profile measurements were performed in a 20 × 20 × 14 cm³ solid‐water phantom using an Exradin W2 scintillation detector and Gafchromic EBT3 film. Dose output constancy for the virtual cone was evaluated over 6 months using an Exradin A11 parallel plate chamber. The photo‐neutron dose generated by these treatments was assessed at distances of 50 and 100 cm from isocenter using a Ludlum Model 30–7 Series Neutron Meter. TGN treatments at TCCC have been previously delivered at 6‐MV FFF using a 5‐mm stereotactic cone. To assess the dosimetric impact of using a virtual cone, eight patients previously treated for TGN with a 5‐mm cone were re‐planned using a virtual cone. Seven patients have now been treated for TGN using a virtual cone at TCCC. Patient‐specific quality assurance was performed for each patient using Gafchromic EBT‐XD film inside a Standard Imaging Stereotactic Dose Verification Phantom. The commissioning results demonstrate that the virtual‐cone dosimetry, first described at UAB, is reproducible on a second Edge linear accelerator at an independent clinical site. The virtual cone is a credible alternative to a physical, stereotactic cone for the treatment of TGN at TCCC.

Multi-level multi-leaf collimators: optimization of layer thicknesses and a feasibility study

PURPOSE

The function of multi-leaf collimators (MLC) is to modulate and shape the intensity of a radiotherapy beam by either blocking or unblocking beamlets. A variation on this functionality is tested in this work wherein the MLC is split into layers, with each layer attenuating the beam by a different amount. In this design, full blocking of a beamlet occurs only if all layers are blocked. This work suggests that such a device, a multi-layer MLC (MLMLC), can deliver dose distributions like a single layer MLC can deliver while requiring less time and monitor units (MU) .

METHODS

Optimal fluences were made for prostate plans using the Eclipse v13.6. An algorithm was developed to create step-and-shoot MLMLC patterns to match these optimal fluences when using up to six layers of MLC. Twelve MLMLC plans were made in total. These patterns were imported back into Eclipse as equivalent tungsten compensators and doses were calculated. Dose volume histogram (DVH) values, total monitor units (MU), and total time to deliver were compared between arc-style MLMLC plans and nine-field step and shoot IMRT plans created completely in Eclipse using a single layer MLC .

RESULTS

When using three or more layers, specified DVH values between the two sets agreed to within 5% while requiring roughly half as much time to deliver and about 20% fewer MU .

CONCLUSIONS

Demonstrated that having multi-layer MLC can deliver dose distributions like a single layer MLC with less time and monitor units. This article is protected by copyright. All rights reserved.

Longitudinal assessment of quality assurance measurements in a 1.5T MR-linac: Part I-Linear accelerator

Purpose

To describe and report longitudinal quality assurance (QA) measurements for the mechanical and dosimetric performance of an Elekta Unity MR‐linac during the first year of clinical use in our institution.

Materials and methods

The mechanical and dosimetric performance of the MR‐linac was evaluated with daily, weekly, monthly, and annual QA testing. The measurements monitor the size of the radiation isocenter, the MR‐to‐MV isocenter concordance, MLC and jaw position, the accuracy and reproducibility of step‐and‐shoot delivery, radiation output and beam profile constancy, and patient‐specific QA for the first 50 treatments in our institution. Results from end‐to‐end QA using anthropomorphic phantoms are also included as a reference for baseline comparisons. Measurements were performed in water or water‐equivalent plastic using ion chambers of various sizes, an ion chamber array, MR‐compatible 2D/3D diode array, portal imager, MRI, and radiochromic film.

Results

The diameter of the radiation isocenter and the distance between the MR/MV isocenters was (μ ± σ) 0.39 ± 0.01 mm and 0.89 ± 0.05 mm, respectively. Trend analysis shows both measurements to be well within the tolerance of 1.0 mm. MLC and jaw positional accuracy was within 1.0 mm while the dosimetric performance of step‐and‐shoot delivery was within 2.0%, irrespective of gantry angle. Radiation output and beam profile constancy were within 2.0% and 1.0%, respectively. End‐to‐end testing performed with ion‐chamber and radiochromic film showed excellent agreement with treatment plan. Patient‐specific QA using a 3D diode array identified gantry angles with low‐pass rates allowing for improvements in plan quality after necessary adjustments.

Conclusion

The MR‐linac operates within the guidelines of current recommendations for linear accelerator performance, stability, and safety. The analysis of the data supports the recently published guidance in establishing clinically acceptable tolerance levels for relative and absolute measurements.

An investigation of using log-file analysis for automated patient-specific quality assurance in MRgRT

Objective

Adaptive radiation therapy (ART) is an integral part of MR‐guided RT (MRgRT), requiring a new RT plan for each treatment fraction and resulting in a significant increase in patient‐specific quality assurance (PSQA). This study investigates the possibility of using treatment log‐file for automated PSQA.

Method

All treatment plans were delivered in 1.5T Unity MR‐Linac (Elekta). A Unity compatible version of LinacView (Standard Imaging) was commissioned to automatically monitor and analyze the log‐files. A total of 220 fields were delivered and measured by ArcCheck^®‐MR (Sun Nuclear) and LinacView. Thirty incorrectly matched fields were also delivered to check for error detection sensitivity. The gamma analysis, γ, with 3%, 3 mm criteria was used in both ArcCheck^®‐MR and LinacView. Additionally, the gantry angle, jaws, and multileaf collimators (MLC) positions reported in the log‐file were compared with plan positions using TG‐142 criteria.

Result

The γ (3%, 3 mm) for the 190 plans were found to be between the range of 72.5%–100.0% and 95.4%–100.0% for ArcCheck^®‐MR and LinacVeiw, respectively. All the delivered gantry angle and jaws were found to be within 0.2° and 2 mm. MLCs that were outside the guard leaves or under the diaphragms were found to have more than 1.0 mm discrepancy. This was attributed to the linac internal override for these MLCs and had no dosimetric impact. Excluding these discrepancies, all MLC positions were found to be within 1.0 mm. The γ (3%, 3 mm) for the 30 incorrectly matched fields were found to be 3.9%–84.8% and 0.1%–64.4% for ArcCheck^®‐MR and LinacVeiw, respectively.

Conclusion

Significant ranked correlation demonstrates the automated log‐file analysis can be used for PSQA and expedite the ART workflow. Ongoing PSQA will be compared with log‐file analysis to investigate the longer term reproducibility and correlation.

AAPM Task Group 198 Report: An implementation guide for TG 142 quality assurance of medical accelerators

The charges on this task group (TG) were as follows: (a) provide specific procedural guidelines for performing the tests recommended in TG 142; (b) provide estimate of the range of time, appropriate personnel, and qualifications necessary to complete the tests in TG 142; and (c) provide sample daily, weekly, monthly, or annual quality assurance (QA) forms. Many of the guidelines in this report are drawn from the literature and are included in the references. When literature was not available, specific test methods reflect the experiences of the TG members (e.g., a test method for door interlock is self-evident with no literature necessary). In other cases, the technology is so new that no literature for test methods was available. Given broad clinical adaptation of volumetric modulated arc therapy (VMAT), which is not a specific topic of TG 142, several tests and criteria specific to VMAT were added.

A tool for patient-specific prediction of delivery discrepancies in machine parameters using trajectory log files

PURPOSE

Multileaf collimator (MLC) delivery discrepancy between planned and actual (delivered) positions have detrimental effect on the accuracy of dose distributions for both IMRT and VMAT. In this study, we evaluated the consistency of MLC delivery discrepancies over the course of treatment and over time to verify that a predictive machine learning model would be applicable throughout the course of treatment. Next, the MLC and gantry positions recorded in prior trajectory log files were analyzed to build a machine learning algorithm to predict MLC positional discrepancies during delivery for a new treatment plan. An open source tool was developed and released to predict the MLC positional discrepancies at treatment delivery for any given plan.

METHODS

Trajectory log files of 142 IMRT plans and 125 VMAT plans from 9 Varian TrueBeam linear accelerators were collected and analyzed. The consistency of delivery discrepancy over patient-specific quality assurance (QA) and patient treatment deliveries was evaluated. Data were binned by treatment site and machine type to determine their relationship with MLC and gantry angle discrepancies. Motion-related parameters including MLC velocity, MLC acceleration, control point, dose rate, and gravity vector, gantry velocity and gantry acceleration, where applicable, were analyzed to evaluate correlations with MLC and gantry discrepancies. Several regression models, such as simple/multiple linear regression, decision tree, and ensemble method (boosted tree and bagged tree model) were used to develop a machine learning algorithm to predict MLC discrepancy based on MLC motion parameters.

RESULTS

MLC discrepancies at patient-specific QA differed from those at patient treatment deliveries by a small (mean = 0.0021 ± 0.0036 mm, P = 0.0089 for IMRT; mean = 0.0010 ± 0.0016 mm, P = 0.0003 for VMAT) but statistically significant amount, likely due to setting the gantry angle to zero for QA in IMRT. MLC motion parameters, MLC velocity and gravity vector, showed significant correlation (P < 0.001) with MLC discrepancy, especially MLC velocity, which had an approximately linear relationship (slope = -0.0027, P < 0.001, R²  = 0.79). Incorporating MLC motion parameters, the final generalized model trained by data from all linear accelerators can predict MLC discrepancy to a high degree of accuracy with high correlation (R²  = 0.86) between predicted and actual MLC discrepancies. The same prediction results were found across different treatment sites and linear accelerators.

CONCLUSION

We have developed a machine learning model using trajectory log files to predict the MLC discrepancies during delivery. This model has been a released as a research tool in which a DICOM-RT with predicted MLC positions can be generated using the original DICOM-RT file as input. This tool can be used to simulate radiotherapy treatment delivery and may be useful for studies evaluating plan robustness and dosimetric uncertainties from treatment delivery.

An error detection method for real-time EPID-based treatment delivery quality assurance

PURPOSE

To quantify the error detection power of a new treatment delivery error detection method. The method validates monitor unit (MU) resolved beam apertures using real-time EPID images.

METHODS

The on-board EPID imager was used to measure cine-EPID (~10 Hz) images for 27 beams from 15 VMAT/SBRT clinical treatment plans and five nonclinical plans. For each frame acquisition, planned apertures were interpolated from the treatment plan multileaf collimator (MLC) positions expected during the frame acquisition interval. Inaccurate deliveries were identified by monitoring in-aperture missed fluence and out-of-aperture excess fluence beyond a specified buffer. Delivery errors were simulated by perturbing the planned MLC positions before comparison with nonperturbed measured apertures. Systematic 1-5 mm MLC leaf shifts were used to train a logistic regression model to determine the error detection threshold. Model accuracy was monitored using tenfold cross-validation. The model's error detection ability was tested with other error modes: plan control point (CP) weight perturbations, collimator rotations, random MLC leaf position errors, EPID imager shift, and stuck MLC leaf. The error detection accuracy was evaluated using the Matthews correlation coefficient (MCC) and the false positive rate (FPR). Per-beam error thresholds of >1, >5, and >10% errant frames were tested to label per-beam errors. The model also was tested for its ability to distinguish five cases with highly similar plans and compared with gamma analysis.

RESULTS

Delivery errors were detected by monitoring intended per-frame images with a 2 mm MLC buffer. Frame-by-frame aperture errors were identified with an optimal threshold of 0.3% of the expected aperture area. The per-frame FPR was 0.02%. The MCC was 1.00 (perfect classification) for detection based on 1% of frames for random CP weight shift, 3 mm random MLC shifts, 90° and 180° collimator rotations, and an MLC leaf stuck after 10% of the beam delivery. The MCC for 2°, 4°, and 8° collimator rotation were 0.53, 0.76, and 0.96, respectively, for the 1% of beam delivery threshold. The 3 mm EPID shift had poor detection, with a minimum MCC of 0.14. The highly similar plans were reliably detected by the aperture check but were not detectable with gamma analysis.

CONCLUSION

The high error detection sensitivity and low FPR makes the aperture check error detection method well suited to pretreatment and during-treatment beam delivery quality assurance (QA). The aperture check detects subtle beam delivery errors, including those resulting from MLC leaf positioning deviations, CP MU shifts, and stuck MLC leaves. Furthermore, the method can distinguish between highly similar treatment plans. Since the aperture check method monitors for the aperture shapes over a given MU interval, it is also sensitive to errors in MU per CP, without requiring dosimetric calibration of the EPID. The aperture check is one part of a Swiss cheese error detection scheme, which provides redundant error testing of multiple error modes, including nonaperture related errors. The rapid error detection, at 1% of a beam's delivery, make the aperture check a potential candidate for QA of on-line adaptive radiotherapy, or other situations in which pretreatment delivery QA is impractical.

Appropriate reduction of the fragmentation level of subfield sequences to improve the accuracy of field delivery in IMRT for nasopharyngeal carcinoma

Objective:

Due to the influence of gravity, inertia and friction, there will be deviation between the position of multileaf collimator (MLC) in the delivered field and the initial intensity modulated radiotherapy (IMRT) plan. This study explores the effects of the fragmentation level of subfield sequences on this deviation and seeks ways to improve the accuracy of field delivery in IMRT for nasopharyngeal carcinoma (NPC).

Methods:

30 patients with NPC were selected, and two groups (groups A and B) of IMRT plans were made in Pinnacle planning system. Different planning parameters were used for optimization so that the subfield sequence fragmentation level of Group B was significantly lower than that of Group A. With the MapCheck2, verification plan was implemented in two ways: 0^o gantry angle and the actual treatment angle, then the differences between the two verification results of each group plan were analyzed.

Results:

The γ-passing rate verified at the actual treatment angle was lower than that of 0^o gantry angle for each group plan, whereas the Group B plan shows small reduction. Mean change value (Δ) was decreased from 1.01% (Group A) to 0.40% (Group B) with 3%/3 mm criteria and 2.88% (Group A) to 1.52% (Group B) with 2%/2 mm criteria, respectively. The smaller the difference (Δ), the actual output dose of the field is more consistent with the original plan. There was no significant correlation between this change and the angle of the field.

Conclusion:

Appropriately reducing the fragmentation level of subfield sequence can reduce the effect of field angle on MLC position and improve the delivery accuracy of IMRT plan.

Advances in knowledge:

The fragmentation level of the subfield sequence may have an impact on the accuracy of the delivery of the plan. This study demonstrates this assumption by comparing the differences between 0° and actual angle verification. Mean change value (Δ) was decreased from Group A to Group B. The smaller the difference (Δ), the actual output dose of the field is more consistent with the original plan. The result of this study may help us to understand that appropriately increasing the subfield area and reducing the fragmentation level of the subfield sequence can reduce the difference between the two verification results, which can further improve the accuracy of the plan delivery in IMRT and tumor treatment.

Use of metrics to quantify IMRT and VMAT treatment plan complexity: A systematic review and perspectives

PURPOSE

Fixed-field intensity modulated radiation therapy (FF-IMRT) or volumetric modulated arc therapy (VMAT) beams complexity is due to fluence fluctuation. Pre-treatment Quality Assurance (PTQA) failure could be linked to it. Several plan complexity metrics (PCM) have been published to quantify this complexity but in a heterogeneous formalism. This review proposes to gather different PCM and to discuss their eventual PTQA failure identifier abilities.

METHODS AND MATERIALS

A systematic literature search and outcome extraction from MEDLINE/PubMed (National Center for Biotechnology Information, NCBI) was performed. First, a list and a synthesis of available PCM is made in a homogeneous formalism. Second, main results relying on the link between PCM and PTQA results but also on other uses are listed.

RESULTS

A total of 163 studies were identified and n = 19 were selected after inclusion and exclusion criteria application. Difference is made between fluence and degree of freedom (DOF)-based PCM. Results about the PCM potential as PTQA failure identifier are described and synthesized. Others uses are also found in quality, big data, machine learning and audit procedure.

CONCLUSIONS

A state of the art is made thanks to this homogeneous PCM classification. For now, PCM should be seen as a planning procedure quality indicator although PTQA failure identifier results are mitigated. However limited clinical use seems possible for some cases. Yet, addressing the general PTQA failure prediction case could be possible with the big data or machine learning help.

Characterization of the HalcyonTM multileaf collimator system

PURPOSE

To characterize the stacked and staggered dual-layer multileaf collimator (MLC) on the Halcyon^TM system.

METHODS

The novel MLC assembly was reviewed and compared to the widely used Millennium^TM 120-leaf MLC system. We investigated the MLC positioning stability over 70 days using Machine Performance Check (MPC) data. We evaluated the leaf transmission, penumbra, leaf end effect, and leaf edge effect. Leaf transmission through distal, proximal, and both MLC layers was measured with a Farmer chamber, by comparing an open and a closed field. Leaf penumbra was measured using film for three different MLC-defined field sizes. The leaf end effect was measured with sweeping gap fields of varying gap sizes defined by the distal MLC. The leaf edge effect was evaluated using the Electronic Portal Imaging Device (EPID) for the different banks, gantry positions, and collimator angles. Point dose measurements for 10 test plans were compared to dose predictions of two dose calculation model versions.

RESULTS

From MPC data, the largest measured MLC positioning accuracy deviation was within 0.1 mm. The proximal MLC exhibited greater deviations compared to the distal MLC. The distal-and-proximal-combination had reduced inter-leaf and intra-leaf transmission compared to delivery with distal-only. The measured leaf transmission was 0.41% for distal-only, 0.40% for proximal-only, and negligible for distal-and-proximal-combination. The leaf end penumbra was wider compared to the leaf edge penumbra. The leaf end effect was measured to be -0.2 mm. The leaf edge effect showed minimal bank, gantry position, and collimator angle dependence. However, a systematic deviation between measurements and treatment planning system handling of the leaf edge effect was observed. The discrepancy between the measured and predicted dose in the 10 test plans improved with the latest version of the dose calculation algorithm.

CONCLUSION

The characteristics of the stacked and staggered dual-layer MLC on the Halcyon^TM system were presented.

Physical and Dosimetric Aspect of Euromechanics Add-on Multileaf Collimator on Varian Clinac 2100 C/D

BACKGROUND

Before treatment planning and dose delivery, quality assurance of multi-leaf collimator (MLC) has an important role in intensity-modulated radiation therapy (IMRT) due to the creation of multiple segments from optimization process.

OBJECTIVE

The purpose of this study is to assess the quality control of MLC leaves using EBT3 Gafchromic films.

MATERIAL AND METHODS

Leaf Position accuracy and leaf gap reproducibility were checked with Garden fence test. The garden fence test consists of 5 thin bands A) 0.2 Cm width spaced at 2 Cm intervals and B) 1 Cm width spaced at 1 Cm intervals. Each leaf accuracy was analyzed with measuring the full-width half-maximum (FWHM). Maximum and average leaf transmission were measured with gafchromic EBT3 films from Ashland for both 6 MV and 18 MV beams.

RESULTS

Leaf positions were found to be in a range between 1.78 - 2.53 mm, instead of nominal 2 mm for the test A and between 9.09 - 10.36 mm, instead of nominal 10 mm for the test B. The Average radiation transmission of the MLC was noted 1.79% and 1.98% of the open 10x10 Cm2 field at isocenter for 6 MV and 18 MV beams, respectively. Maximum radiation transmission was noted 4.1% and 4.4% for 6 MV and 18 MV beams, respectively.

CONCLUSION

In this study, application of gafchromic EBT3 films for the quality assurance of Euromechanics multileaf collimator was studied. Our results showed that the average leaf leakage and positional accuracy of this type of MLC were in the acceptance level based on the Protocols.

Evaluation of the correlation between prostatic displacement and rectal deformation using the Dice similarity coefficient of the rectum

To estimate the relationship between the three-dimensional (3D) displacement error of the prostate and rectal deformation for reduction of deviation between the planned and treatment dose, using multiple acquisition planning CT (MPCT) and the Dice similarity coefficient (DSC) for rectal deformation for treatment of patients with prostate cancer. The 3D displacement error between the pelvic bone and a matching fiducial marker was calculated using MPCT in 24 patients who underwent prostate volumetric-modulated arc therapy for prostate cancer. We calculated the 3D displacement error between the pelvic bone and a matching fiducial marker on MPCT. The correlation of the 3D displacement error with the DSC of the rectum, calculated from MPCT images, was evaluated based on deformable image registration. The 3D displacement error of the prostate showed a slight correlation between MPCT and cone-beam computed tomography (adjusted r² = 0.241). The 3D displacement error, based on the pelvic bone and a fiducial marker on MPCT images, showed a moderate correlation with the DSC of the rectum (adjusted r² = 0.645) and was improved by a mean of 3.94 mm, based on MPCT, during the treatment period. The 3D displacement error on MPCT correlates with the 3D displacement error of daily cone-beam computed tomography; optimal selection of MPCT can potentially facilitate on-board setup of prostate patients to enable more accurate radiotherapy. The advance information of the 3D displacement error and rectal deformation is useful for optimal planning CT that can minimize the deviation between the planned dose and the treatment dose in patients receiving treatment for prostate cancer.

MLC positioning verification for small fields: a new investigation into automatic EPID-based verification methods

Multileaf-collimator (MLC) defined small fields in radiotherapy are used in high dose, ultra-conformal techniques such as stereotactic radiotherapy and stereotactic radiosurgery. Proximity to critical structures and irreversible damage arising from inaccurate delivery mean that correct positioning of the MLC system is of the utmost importance. Some of the existing techniques for MLC positioning quality assurance make use of electronic portal imaging device (EPID) images. However, conventional collimation verification algorithms based on the full width at half maximum (FWHM) fail when applied to small field images acquired by an EPID due to overlapping aperture penumbrae, lateral electron disequilibrium and radiation source occlusion. The objective of this study was to investigate sub-pixel edge detection and other techniques with the aim of developing an automatic and autonomous EPID-based method suitable for MLC positional verification of small static fields with arbitrary shapes. Methods investigated included derivative interpolation, Laplacian of Gaussian (LoG) and an algorithm based on the partial area effect hypothesis. None of these methods were found to be suitable for MLC positioning verification in small field conditions. A method is proposed which uses a manufacturer-specific empirically modified FWHM algorithm which shows improvement over the conventional techniques in the small field size range. With a measured mean absolute difference from planned position for Varian linacs of 0.01 ± 0.26 mm, compared with the erroneous FWHM value of 0.70 ± 0.51 mm. For Elekta linacs the proposed algorithm returned 0.26 ± 0.25 mm, in contrast to the FWHM result of 1.79 ± 1.07 mm.

A quantitative method to the analysis of MLC leaf position and speed based on EPID and EBT3 film for dynamic IMRT treatment with different types of MLC

A quantitative method based on the electronic portal imaging system (EPID) and film was developed for MLC position and speed testing; this method was used for three MLC types (Millennium, MLCi, and Agility MLC). To determine the leaf position, a picket fence designed by the dynamic (DMLC) model was used. The full‐width half‐maximum (FWHM) values of each gap measured by EPID and EBT3 were converted to the gap width using the FWHM versus nominal gap width relationship. The algorithm developed for the picket fence analysis was able to quantify the gap width, the distance between gaps, and each individual leaf position. To determine the leaf speed, a 0.5 × 20 cm²MLC‐defined sliding gap was applied across a 14 × 20 cm² symmetry field. The linacs ran at a fixed‐dose rate. The use of different monitor units (MUs) for this test led to different leaf speeds. The effect of leaf transmission was considered in a speed accuracy analysis. The difference between the EPID and film results for the MLC position is less than 0.1 mm. For the three MLC types, twice the standard deviation (2 SD) is provided; 0.2, 0.4, and 0.4 mm for gap widths of three MLC types, and 0.1, 0.2, and 0.2 mm for distances between gaps. The individual leaf positions deviate from the preset positions within 0.1 mm. The variations in the speed profiles for the EPID and EBT3 results are consistent, but the EPID results are slightly better than the film results. Different speeds were measured for each MLC type. For all three MLC types, speed errors increase with increasing speed. The analysis speeds deviate from the preset speeds within approximately 0.01 cm s⁻¹. This quantitative analysis of MLC position and speed provides an intuitive evaluation for MLC quality assurance (QA).

Evaluation of MLC performance in VMAT and dynamic IMRT by log file analysis

PURPOSE

This multi-institution study assessed the positioning accuracy of multileaf collimators (MLC) by analyzing log files. It determined the main machine parameters that affect MLC positioning errors for pre-TrueBeam (Clinac) and TrueBeam linacs.

METHODS

Around 30,000 dIMRT and VMAT log files belonging to 6 linacs from 4 different centers were analyzed. An in-house software was used to calculate 95th percentile and RMS error values and their correlation with certain parameters such as maximum leaf speed, mean leaf speed and gantry angle. The effect of MLC communication delay on error statistics was assessed in Clinac linacs. To that end MLC positioning error statistics were calculated with and without the delay effect.

RESULTS

For dIMRT treatments in Clinac linacs the mean leaf RMS error was 0.306mm with and 0.030mm without the delay effect. Leaf RMS error was closely linked to maximum and mean leaf speeds, but without the delay effect that link was weaker. No trend was observed between bank RMS error and gantry angle. Without the delay effect larger bank RMS errors were obtained for gantry angles with leaf movements against gravity. For VMAT treatments in TrueBeam linacs the mean leaf RMS error was 0.038mm. A link was also observed between leaf RMS error and maximum and mean leaf speeds.

CONCLUSION

TrueBeam MLC positioning errors are substantially lower than those of Clinac linacs. In Clinac machines the analysis of dynalogs without the delay effect allows us to study the influence of factors that are masked by the delay effect.

Automatic detection of MLC relative position errors for VMAT using the EPID-based picket fence test

Multi-leaf collimators (MLCs) ensure the accurate delivery of treatments requiring complex beam fluences like intensity modulated radiotherapy and volumetric modulated arc therapy. The purpose of this work is to automate the detection of MLC relative position errors  ⩾0.5 mm using electronic portal imaging device-based picket fence tests and compare the results to the qualitative assessment currently in use. Picket fence tests with and without intentional MLC errors were measured weekly on three Varian linacs. The picket fence images analysed covered a time period ranging between 14-20 months depending on the linac. An algorithm was developed that calculated the MLC error for each leaf-pair present in the picket fence images. The baseline error distributions of each linac were characterised for an initial period of 6 months and compared with the intentional MLC errors using statistical metrics. The distributions of median and one-sample Kolmogorov-Smirnov test p-value exhibited no overlap between baseline and intentional errors and were used retrospectively to automatically detect MLC errors in routine clinical practice. Agreement was found between the MLC errors detected by the automatic method and the fault reports during clinical use, as well as interventions for MLC repair and calibration. In conclusion the method presented provides for full automation of MLC quality assurance, based on individual linac performance characteristics. The use of the automatic method has been shown to provide early warning for MLC errors that resulted in clinical downtime.

An EPID-based system for gantry-resolved MLC quality assurance for VMAT

Multileaf collimator (MLC) positions should be precisely and independently mea-sured as a function of gantry angle as part of a comprehensive quality assurance (QA) program for volumetric-modulated arc therapy (VMAT). It is also ideal that such a QA program has the ability to relate MLC positional accuracy to patient-specific dosimetry in order to determine the clinical significance of any detected MLC errors. In this work we propose a method to verify individual MLC trajectories during VMAT deliveries for use as a routine linear accelerator QA tool. We also extend this method to reconstruct the 3D patient dose in the treatment planning sys-tem based on the measured MLC trajectories and the original DICOM plan file. The method relies on extracting MLC positions from EPID images acquired at 8.41fps during clinical VMAT deliveries. A gantry angle is automatically tagged to each image in order to obtain the MLC trajectories as a function of gantry angle. This analysis was performed for six clinical VMAT plans acquired at monthly intervals for three months. The measured trajectories for each delivery were compared to the MLC positions from the DICOM plan file. The maximum mean error detected was 0.07 mm and a maximum root-mean-square error was 0.8 mm for any leaf of any delivery. The sensitivity of this system was characterized by introducing random and systematic MLC errors into the test plans. It was demonstrated that the system is capable of detecting random and systematic errors on the range of 1-2mm and single leaf calibration errors of 0.5 mm. The methodology developed in the work has potential to be used for efficient routine linear accelerator MLC QA and pretreatment patient-specific QA and has the ability to relate measured MLC positional errors to 3D dosimetric errors within a patient volume.

Quantification of residual dose estimation error on log file-based patient dose calculation

PURPOSE

The log file-based patient dose estimation includes a residual dose estimation error caused by leaf miscalibration, which cannot be reflected on the estimated dose. The purpose of this study is to determine this residual dose estimation error.

METHODS AND MATERIALS

Modified log files for seven head-and-neck and prostate volumetric modulated arc therapy (VMAT) plans simulating leaf miscalibration were generated by shifting both leaf banks (systematic leaf gap errors: ±2.0, ±1.0, and ±0.5mm in opposite directions and systematic leaf shifts: ±1.0mm in the same direction) using MATLAB-based (MathWorks, Natick, MA) in-house software. The generated modified and non-modified log files were imported back into the treatment planning system and recalculated. Subsequently, the generalized equivalent uniform dose (gEUD) was quantified for the definition of the planning target volume (PTV) and organs at risks.

RESULTS

For MLC leaves calibrated within ±0.5mm, the quantified residual dose estimation errors that obtained from the slope of the linear regression of gEUD changes between non- and modified log file doses per leaf gap are in head-and-neck plans 1.32±0.27% and 0.82±0.17Gy for PTV and spinal cord, respectively, and in prostate plans 1.22±0.36%, 0.95±0.14Gy, and 0.45±0.08Gy for PTV, rectum, and bladder, respectively.

CONCLUSIONS

In this work, we determine the residual dose estimation errors for VMAT delivery using the log file-based patient dose calculation according to the MLC calibration accuracy.

A machine learning approach to the accurate prediction of multi-leaf collimator positional errors

Discrepancies between planned and delivered movements of multi-leaf collimators (MLCs) are an important source of errors in dose distributions during radiotherapy. In this work we used machine learning techniques to train models to predict these discrepancies, assessed the accuracy of the model predictions, and examined the impact these errors have on quality assurance (QA) procedures and dosimetry. Predictive leaf motion parameters for the models were calculated from the plan files, such as leaf position and velocity, whether the leaf was moving towards or away from the isocenter of the MLC, and many others. Differences in positions between synchronized DICOM-RT planning files and DynaLog files reported during QA delivery were used as a target response for training of the models. The final model is capable of predicting MLC positions during delivery to a high degree of accuracy. For moving MLC leaves, predicted positions were shown to be significantly closer to delivered positions than were planned positions. By incorporating predicted positions into dose calculations in the TPS, increases were shown in gamma passing rates against measured dose distributions recorded during QA delivery. For instance, head and neck plans with 1%/2 mm gamma criteria had an average increase in passing rate of 4.17% (SD = 1.54%). This indicates that the inclusion of predictions during dose calculation leads to a more realistic representation of plan delivery. To assess impact on the patient, dose volumetric histograms (DVH) using delivered positions were calculated for comparison with planned and predicted DVHs. In all cases, predicted dose volumetric parameters were in closer agreement to the delivered parameters than were the planned parameters, particularly for organs at risk on the periphery of the treatment area. By incorporating the predicted positions into the TPS, the treatment planner is given a more realistic view of the dose distribution as it will truly be delivered to the patient.

A multi-institution evaluation of MLC log files and performance in IMRT delivery

Background

The multileaf collimator (MLC) is a critical component to accurate intensity-modulated radiotherapy (IMRT) delivery. This study examined MLC positional accuracy via MLC logs from Varian machines from six institutions and three delivery techniques to evaluate typical positional accuracy and treatment and mechanical parameters that affect accuracy. Typical accuracy achieved was compared against TG-142 recommendations for MLC performance; more appropriate recommendations are suggested.

Methods

Over 85,000 Varian MLC treatment logs were collected from six institutions and analyzed with FractionCHECK. Data were binned according to institution and treatment type to determine overall root mean square (RMS) and 95^th percentile error values, and then to look for correlations between those errors and with mechanical and treatment parameters including mean and maximum leaf speed, gantry angle, beam-on time, mean leaf error, and number of segments.

Results

Results of treatment logs found that leaf RMS error and 95^th percentile leaf error were consistent between institutions, but varied by treatment type. The step and shoot technique had very small errors: the mean RMS leaf error was 0.008 mm. For dynamic treatments the mean RMS leaf error was 0.32 mm, while volumetric-modulated arc treatment (VMAT) showed an RMS leaf error of 0.46 mm. Most MLC leaf errors were found to be well below TG-142 recommended tolerances. For the dynamic and VMAT techniques, the mean and maximum leaf speeds were significantly linked to the leaf RMS error. Additionally, for dynamic delivery, the mean leaf error was correlated with RMS error, whereas for VMAT the average gantry speed was correlated. For all treatments, the RMS error and the 95^th percentile leaf error were correlated.

Conclusions

Restricting the maximum leaf speed can help improve MLC performance for dynamic and VMAT deliveries. Furthermore, the tolerances of leaf RMS and error counts for all treatment types should be tightened from the TG-142 values to make them more appropriate for clinical performance. Values of 1 mm for the 95^th percentile of leaf RMS error and 1.5 mm for the 95^th percentile leaf error are suggested as action levels for all treatment types.

Quality, technology and outcomes: evolution and evaluation of new treatments and/or new technology

The pace of technological innovation and adoption continues to increase each year, and the field of Radiation Oncology struggles to react appropriately to the changes and potential improvements in treatment which hopefully will result from this innovation. The standard methods used in the past to test new technology and treatment techniques are often no longer appropriate for this fast-changing environment. This paper uses examples from radiotherapy technological developments over the last decades to illustrate issues which need to be solved in order to study and evaluate potential advances, and then describes several improved ways to study new techniques and technology. Design of appropriate studies can help us improve patient care while at the same time documenting which new clinical strategies, enabled by new technology, lead to improved patient outcomes.

Simplified field-in-field technique for a large-scale implementation in breast radiation treatment

We wanted to evaluate a simplified "field-in-field" technique (SFF) that was implemented in our department of Radiation Oncology for breast treatment. This study evaluated 15 consecutive patients treated with a simplified field in field technique after breast-conserving surgery for early-stage breast cancer. Radiotherapy consisted of whole-breast irradiation to the total dose of 50 Gy in 25 fractions, and a boost of 16 Gy in 8 fractions to the tumor bed. We compared dosimetric outcomes of SFF to state-of-the-art electronic surface compensation (ESC) with dynamic leaves. An analysis of early skin toxicity of a population of 15 patients was performed. The median volume receiving at least 95% of the prescribed dose was 763 mL (range, 347-1472) for SFF vs. 779 mL (range, 349-1494) for ESC. The median residual 107% isodose was 0.1 mL (range, 0-63) for SFF and 1.9 mL (range, 0-57) for ESC. Monitor units were on average 25% higher in ESC plans compared with SFF. No patient treated with SFF had acute side effects superior to grade 1-NCI scale. SFF created homogenous 3D dose distributions equivalent to electronic surface compensation with dynamic leaves. It allowed the integration of a forward planned concomitant tumor bed boost as an additional multileaf collimator subfield of the tangential fields. Compared with electronic surface compensation with dynamic leaves, shorter treatment times allowed better radiation protection to the patient. Low-grade acute toxicity evaluated weekly during treatment and 2 months after treatment completion justified the pursuit of this technique for all breast patients in our department.

Physical and dosimetric characteristic of high-definition multileaf collimator (HDMLC) for SRS and IMRT

Physical and dosimetric characteristics of HDMLC were studied for SRS6, 6, and 10 MV X‐rays from Novalis Tx. This in‐built tertiary collimator consists of 60 pairs (32×0.25 cm; 26×0.5 cm and 2×0.7 cm) of leaves. Properties of HDMLC studied included alignment, readout and radiation field congruence, radiation penumbra, accuracy and reproducibility of leaf position and gap width, static and dynamic leaf shift, tongue‐and‐groove effect, leaf transmission and leakage, leaf travel speed, and delivery of dynamic conformal arc and IMRT. All tests were performed using a calibrated ionization chamber, film dosimetry and DynaLog file analysis. Alignment of leaves with isocenter plane was better than 0.03 cm at all gantry and collimator positions. The congruence of HDMLC readout and radiation field agreed to within ± 0.03cm for filed sizes ranging from 1×1 to 20×20 cm2. Mean 80% to 20% penumbra width parallel (perpendicular) to leaf motion was 0.24±0.05(0.21±0.02) cm, 0.37±0.12(0.29±0.07) cm, and 0.51±0.13(0.43±0.07) cm for SRS6, 6, and 10 MV X‐rays, respectively. Circular field penumbra was comparable to corresponding square field. Average penumbra of 1×20 cm2 field was effectively constant over off‐axis positions of up to 12 cm with mean value of 0.16 (± 0.01)cm at 1.5 cm depth and 0.38 (± 0.04)cm at 10 cm depth. Minimum and maximum effective penumbra along the straight diagonal edge of irregular fields increased from 0.3 and 0.32 cm at 70° steep angle to 0.35 and 0.56 cm at 20° steep angle. Modified Picket Fence test showed average FWHM of 0.18 cm and peak‐to‐peak distance of 1.99 cm for 0.1 cm band and 2 cm interband separation. Dynamic multileaf collimation (DMLC) output factor remained within ± 1% for 6 MV and ± 0.5% for 10 MV X‐rays at all gantry positions, and was reproducible within ± 0.5% over a period of 14 months. The static leaf shift was 0.03 cm for all energies, while dynamic leaf shift was 0.044 cm for 10 MV and 0.039 cm for both SRS6 and 6 MV X‐rays. The dose depression and corresponding tongue‐and‐groove size were 24% and 0.17 cm for 6 MV and 19% and 0.20 cm for 10 MV X‐rays. Average transmission through HDMLC was 1.09%, 1.14% and 1.34% for SRS6, 6 and 10 MV X‐rays. Analysis of DynaLog files for leaf speed test in arc dynamic mode, delivery test of dynamic conformal arc, and step‐and‐shoot and sliding window IMRT showed at least 95% or more of the error counts had misplacements < 0.2cm, with maximum root mean square (RMS) error value calculated at 0.13 cm. Accurate and reproducible leaf position and gap width, and less leakage and small consistent penumbra over the fields demonstrate HDMLC suitable for high‐dose resolution SRS and IMRT.

PACS number: 87.56.N‐, 87.55.Qr, 87.50.cm, 87.55.de, 87.53.Ly

Failure mode and effect analysis-based quality assurance for dynamic MLC tracking systems

PURPOSE

To develop and implement a failure mode and effect analysis (FMEA)-based commissioning and quality assurance framework for dynamic multileaf collimator (DMLC) tumor tracking systems.

METHODS

A systematic failure mode and effect analysis was performed for a prototype real-time tumor tracking system that uses implanted electromagnetic transponders for tumor position monitoring and a DMLC for real-time beam adaptation. A detailed process tree of DMLC tracking delivery was created and potential tracking-specific failure modes were identified. For each failure mode, a risk probability number (RPN) was calculated from the product of the probability of occurrence, the severity of effect, and the detectibility of the failure. Based on the insights obtained from the FMEA, commissioning and QA procedures were developed to check (i) the accuracy of coordinate system transformation, (ii) system latency, (iii) spatial and dosimetric delivery accuracy, (iv) delivery efficiency, and (v) accuracy and consistency of system response to error conditions. The frequency of testing for each failure mode was determined from the RPN value.

RESULTS

Failures modes with RPN > or = 125 were recommended to be tested monthly. Failure modes with RPN < 125 were assigned to be tested during comprehensive evaluations, e.g., during commissioning, annual quality assurance, and after major software/hardware upgrades. System latency was determined to be approximately 193 ms. The system showed consistent and accurate response to erroneous conditions. Tracking accuracy was within 3%-3 mm gamma (100% pass rate) for sinusoidal as well as a wide variety of patient-derived respiratory motions. The total time taken for monthly QA was approximately 35 min, while that taken for comprehensive testing was approximately 3.5 h.

CONCLUSIONS

FMEA proved to be a powerful and flexible tool to develop and implement a quality management (QM) framework for DMLC tracking. The authors conclude that the use of FMEA-based QM ensures efficient allocation of clinical resources because the most critical failure modes receive the most attention. It is expected that the set of guidelines proposed here will serve as a living document that is updated with the accumulation of progressively more intrainstitutional and interinstitutional experience with DMLC tracking.

Task Group 142 report: quality assurance of medical accelerators

The task group (TG) for quality assurance of medical accelerators was constituted by the American Association of Physicists in Medicine's Science Council under the direction of the Radiation Therapy Committee and the Quality Assurance and Outcome Improvement Subcommittee. The task group (TG-142) had two main charges. First to update, as needed, recommendations of Table II of the AAPM TG-40 report on quality assurance and second, to add recommendations for asymmetric jaws, multileaf collimation (MLC), and dynamic/virtual wedges. The TG accomplished the update to TG-40, specifying new test and tolerances, and has added recommendations for not only the new ancillary delivery technologies but also for imaging devices that are part of the linear accelerator. The imaging devices include x-ray imaging, photon portal imaging, and cone-beam CT. The TG report was designed to account for the types of treatments delivered with the particular machine. For example, machines that are used for radiosurgery treatments or intensity-modulated radiotherapy (IMRT) require different tests and/or tolerances. There are specific recommendations for MLC quality assurance for machines performing IMRT. The report also gives recommendations as to action levels for the physicists to implement particular actions, whether they are inspection, scheduled action, or immediate and corrective action. The report is geared to be flexible for the physicist to customize the QA program depending on clinical utility. There are specific tables according to daily, monthly, and annual reviews, along with unique tables for wedge systems, MLC, and imaging checks. The report also gives specific recommendations regarding setup of a QA program by the physicist in regards to building a QA team, establishing procedures, training of personnel, documentation, and end-to-end system checks. The tabulated items of this report have been considerably expanded as compared with the original TG-40 report and the recommended tolerances accommodate differences in the intended use of the machine functionality (non-IMRT, IMRT, and stereotactic delivery).

Quality assurance needs for modern image-based radiotherapy: recommendations from 2007 interorganizational symposium on "quality assurance of radiation therapy: challenges of advanced technology"

This report summarizes the consensus findings and recommendations emerging from 2007 Symposium, "Quality Assurance of Radiation Therapy: Challenges of Advanced Technology." The Symposium was held in Dallas February 20-22, 2007. The 3-day program, which was sponsored jointly by the American Society for Therapeutic Radiology and Oncology (ASTRO), American Association of Physicists in Medicine (AAPM), and National Cancer Institute (NCI), included >40 invited speakers from the radiation oncology and industrial engineering/human factor communities and attracted nearly 350 attendees, mostly medical physicists. A summary of the major findings follows. The current process of developing consensus recommendations for prescriptive quality assurance (QA) tests remains valid for many of the devices and software systems used in modern radiotherapy (RT), although for some technologies, QA guidance is incomplete or out of date. The current approach to QA does not seem feasible for image-based planning, image-guided therapies, or computer-controlled therapy. In these areas, additional scientific investigation and innovative approaches are needed to manage risk and mitigate errors, including a better balance between mitigating the risk of catastrophic error and maintaining treatment quality, complimenting the current device-centered QA perspective by a more process-centered approach, and broadening community participation in QA guidance formulation and implementation. Industrial engineers and human factor experts can make significant contributions toward advancing a broader, more process-oriented, risk-based formulation of RT QA. Healthcare administrators need to appropriately increase personnel and ancillary equipment resources, as well as capital resources, when new advanced technology RT modalities are implemented. The pace of formalizing clinical physics training must rapidly increase to provide an adequately trained physics workforce for advanced technology RT. The specific recommendations of the Symposium included the following. First, the AAPM, in cooperation with other advisory bodies, should undertake a systematic program to update conventional QA guidance using available risk-assessment methods. Second, the AAPM advanced technology RT Task Groups should better balance clinical process vs. device operation aspects--encouraging greater levels of multidisciplinary participation such as industrial engineering consultants and use-risk assessment and process-flow techniques. Third, ASTRO should form a multidisciplinary subcommittee, consisting of physician, physicist, vendor, and industrial engineering representatives, to better address modern RT quality management and QA needs. Finally, government and private entities committed to improved healthcare quality and safety should support research directed toward addressing QA problems in image-guided therapies.